tommy/libpostal
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

[languages/osm] Adding a primitive phrase dictionary to the OSM training data construction script and a few heuristics to help disambiguate in the case of small local language groups that may not be specified with name:lang tags e.g. Occitan, Catalan, Basque, Galician, etc. Also throwing away ambiguous multilanguage names

Browse Source
This commit is contained in:
Al
2015-08-18 11:12:27 -04:00
parent fb7f2999e5
commit 0e00625dbd
1 changed files with 170 additions and 10 deletions
Download Patch File Download Diff File Expand all files Collapse all files

180
scripts/geodata/osm/osm_address_training_data.py
View File

@@ -11,7 +11,7 @@ import tempfile
import ujson as json
import yaml
from collections import defaultdict
from collections import defaultdict, OrderedDict
from lxml import etree
from itertools import ifilter, chain
@@ -21,8 +21,12 @@ sys.path.append(os.path.realpath(os.path.join(os.pardir, os.pardir)))
sys.path.append(os.path.realpath(os.path.join(os.pardir, os.pardir, os.pardir, 'python')))
from address_normalizer.text.tokenize import *
from address_normalizer.text.normalize import PhraseFilter
from geodata.i18n.languages import *
from geodata.polygons.language_polys import *
from geodata.i18n.unicode_paths import DATA_DIR
from marisa_trie import BytesTrie
from geodata.csv_utils import *
from geodata.file_utils import *
@@ -43,6 +47,8 @@ PLANET_WAYS_OUTPUT_FILE = 'planet-ways.tsv'
PLANET_VENUES_INPUT_FILE = 'planet-venues.osm'
PLANET_VENUES_OUTPUT_FILE = 'planet-venues.tsv'
DICTIONARIES_DIR = os.path.join(DATA_DIR, 'dictionaries')
ALL_OSM_TAGS = set(['node', 'way', 'relation'])
WAYS_RELATIONS = set(['way', 'relation'])
@@ -73,6 +79,91 @@ osm_fields = [
]
PREFIX_KEY = u'\x02'
SUFFIX_KEY = u'\x03'
POSSIBLE_ROMAN_NUMERALS = set(['i', 'ii', 'iii', 'iv', 'v', 'vi', 'vii', 'viii', 'ix',
'x', 'xi', 'xii', 'xiii', 'xiv', 'xv', 'xvi', 'xvii', 'xviii', 'xix',
'xx', 'xxx', 'xl', 'l', 'lx', 'lxx', 'lxxx', 'xc',
'c', 'cc', 'ccc', 'cd', 'd', 'dc', 'dcc', 'dccc', 'cm',
'm', 'mm', 'mmm', 'mmmm'])
class StreetTypesGazetteer(PhraseFilter):
def serialize(self, s):
return s
def deserialize(self, s):
return s
def configure(self, base_dir=DICTIONARIES_DIR):
kvs = defaultdict(OrderedDict)
for lang in os.listdir(DICTIONARIES_DIR):
for filename in ('street_types.txt', 'directionals.txt'):
path = os.path.join(DICTIONARIES_DIR, lang, filename)
if not os.path.exists(path):
continue
for line in open(path):
line = line.strip()
if not line:
continue
canonical = safe_decode(line.split('|')[0])
if canonical in POSSIBLE_ROMAN_NUMERALS:
continue
kvs[canonical][lang] = None
for filename in ('concatenated_suffixes_separable.txt', 'concatenated_suffixes_inseparable.txt', 'concatenated_prefixes_separable.txt'):
path = os.path.join(DICTIONARIES_DIR, lang, filename)
if not os.path.exists(path):
continue
for line in open(path):
line = line.strip()
if not line:
continue
canonical = safe_decode(line.split('|')[0])
if 'suffixes' in filename:
canonical = SUFFIX_KEY + canonical[::-1]
else:
canonical = PREFIX_KEY + canonical
kvs[canonical][lang] = None
kvs = [(k, v) for k, vals in kvs.iteritems() for v in vals.keys()]
self.trie = BytesTrie(kvs)
self.configured = True
def search_substring(self, s):
if len(s) == 0:
return None
for i in xrange(len(s) + 1):
if not self.trie.has_keys_with_prefix(s[:i]):
i -= 1
break
if i > 0:
return self.trie.get(s[:i])
else:
return None
def filter(self, *args, **kw):
for c, t, data in super(StreetTypesGazetteer, self).filter(*args):
if c != token_types.PHRASE:
suffix_search = self.search_substring(SUFFIX_KEY + t[1][::-1])
if suffix_search:
yield (token_types.PHRASE, [(c, t)], suffix_search)
continue
prefix_search = self.search_substring(PREFIX_KEY + t[1])
if prefix_search:
yield (token_types.PHRASE, [(c, t)], prefix_search)
continue
yield c, t, data
street_types_gazetteer = StreetTypesGazetteer()
# Currently, all our data sets are converted to nodes with osmconvert before parsing
def parse_osm(filename, allowed_types=ALL_OSM_TAGS):
f = open(filename)
@@ -331,15 +422,51 @@ def latlon_to_floats(latitude, longitude):
return float(latitude), float(longitude)
UNKNOWN_LANGUAGE = 'unk'
AMBIGUOUS_LANGUAGE = 'xxx'
def disambiguate_language(text, languages):
valid_languages = OrderedDict([(l['lang'], l['default']) for l in languages])
tokens = tokenize(safe_decode(text).replace(u'-', u' ').lower())
current_language = None
for c, t, data in street_types_gazetteer.filter(tokens):
if c == token_types.PHRASE:
valid = [lang for lang in data if lang in valid_languages]
if len(valid) != 1:
continue
phrase_lang = valid[0]
if phrase_lang != current_language and current_language is not None:
return AMBIGUOUS_LANGUAGE
current_language = phrase_lang
if current_language is not None:
return current_language
return UNKNOWN_LANGUAGE
def country_and_languages(language_rtree, latitude, longitude):
props = language_rtree.point_in_poly(latitude, longitude, return_all=True)
if not props:
return None, None
return None, None, None
country = props[0]['qs_iso_cc'].lower()
languages = list(chain(*(p['languages'] for p in props)))
languages = []
for p in props:
languages.extend(p['languages'])
# Python's builtin sort is stable, so if there are two defaults, the first remains first
# Since polygons are returned from the index ordered from smallest admin level to largest,
# it means the default language of the region overrides the country default
default_languages = sorted(languages, key=operator.itemgetter('default'), reverse=True)
return country, default_languages
return country, default_languages, props
WELL_REPRESENTED_LANGUAGES = set(['en', 'fr', 'it', 'de', 'nl', 'es'])
def get_language_names(language_rtree, key, value, tag_prefix='name'):
@@ -355,22 +482,53 @@ def get_language_names(language_rtree, key, value, tag_prefix='name'):
except Exception:
return None, None
country, candidate_languages = country_and_languages(language_rtree, latitude, longitude)
country, candidate_languages, language_props = country_and_languages(language_rtree, latitude, longitude)
if not (country and candidate_languages):
return None, None
num_defaults = sum((1 for l in candidate_languages if l.get('default')))
num_langs = len(candidate_languages)
default_langs = set([l['lang'] for l in candidate_languages if l.get('default')])
num_defaults = len(default_langs)
name_language = defaultdict(list)
has_alternate_names = any((k.startswith(tag_prefix + ':') and normalize_osm_name_tag(k, script=True)
in languages for k, v in value.iteritems()))
regional_defaults = 0
country_defaults = 0
regional_langs = set()
country_langs = set()
for p in language_props:
if p['admin_level'] > 0:
regional_defaults += sum((1 for lang in p['languages'] if lang.get('default')))
regional_langs |= set([l['lang'] for l in p['languages']])
else:
country_defaults += sum((1 for lang in p['languages'] if lang.get('default')))
country_langs |= set([l['lang'] for l in p['languages']])
for k, v in value.iteritems():
if k.startswith(tag_prefix + ':'):
norm = normalize_osm_name_tag(k)
norm_sans_script = normalize_osm_name_tag(k, script=True)
if norm in languages or norm_sans_script in languages:
name_language[norm].append(v)
elif not has_alternate_names and num_defaults == 1 and k.startswith(tag_first_component) and (has_colon or ':' not in k) and normalize_osm_name_tag(k, script=True) == tag_last_component:
name_language[candidate_languages[0]['lang']].append(v)
elif not has_alternate_names and k.startswith(tag_first_component) and (has_colon or ':' not in k) and normalize_osm_name_tag(k, script=True) == tag_last_component:
if num_langs == 1:
name_language[candidate_languages[0]['lang']].append(v)
else:
lang = disambiguate_language(v, candidate_languages)
default_lang = candidate_languages[0]['lang']
if lang == AMBIGUOUS_LANGUAGE:
print u'Ambiguous language. country={}, default={}, str={}'.format(country, default_lang, v)
return None, None
elif lang == UNKNOWN_LANGUAGE and num_defaults == 1:
name_language[default_lang].append(v)
elif lang != UNKNOWN_LANGUAGE:
if lang != default_lang and lang in country_langs and country_defaults > 1 and regional_defaults > 0 and lang in WELL_REPRESENTED_LANGUAGES:
return None, None
name_language[lang].append(v)
else:
return None, None
return country, name_language
@@ -423,7 +581,7 @@ def build_address_format_training_data(language_rtree, infile, out_dir):
except Exception:
continue
country, default_languages = country_and_languages(language_rtree, latitude, longitude)
country, default_languages, language_props = country_and_languages(language_rtree, latitude, longitude)
if not (country and default_languages):
continue
@@ -469,7 +627,7 @@ def build_address_format_training_data_limited(language_rtree, infile, out_dir):
except Exception:
continue
country, default_languages = country_and_languages(language_rtree, latitude, longitude)
country, default_languages, language_props = country_and_languages(language_rtree, latitude, longitude)
if not (country and default_languages):
continue
@@ -591,6 +749,8 @@ if __name__ == '__main__':
language_rtree = LanguagePolygonIndex.load(args.rtree_dir)
street_types_gazetteer.configure()
# Can parallelize
if args.streets_file:
build_ways_training_data(language_rtree, args.streets_file, args.out_dir)